The lithography process for fabricating semiconductor devices can be broken down into three general steps: coating; align/expose, develop. After the develop step is completed, the wafer is inspected for defects which may have occurred in any of the three lithography process areas. Typical defects include problems with photo resist or ARC/BARC coating, edge bead processing, exposure, alignment, development, as well as defects caused by contamination or handling, such as particles or scratches.
Although the chance of misprocessing at any single lithography step is small, a typical wafer goes through 20 to 25 lithography steps. Excursions due to process equipment problems, mishandling, and contamination can occur at each of these steps, so the cumulative probability of a wafer experiencing a yield-limiting defect becomes significant. While most defects impact only a small area of the wafer and do not require rework, some defects impact 30% or more of the wafer. These are defined as global defects. After develop inspection (ADI) procedures detect, classify, and disposition wafers with global lithography defects for rework. Each recovered wafer can result in savings of thousands, or even tens of thousands of dollars, in revenue.
The vast majority of economically re-workable defects are macro-scale, as they are very large relative to the transistors and interconnect structures in the device. Because of their large size, trained operators at microscope stations have traditionally detected macro defects visually. Since manual inspection is a relatively slow process compared to track and stepper throughput, visual inspection has typically been performed on a limited lot-to-lot or within-lot sampling basis. Automating the ADI process for improved throughput has been a challenging problem, as macro defects vary widely in size, type, and appearance, requiring sensitive detection and sophisticated automatic defect classification systems.
In typical systems, after various coating, align/expose, and develop steps, the wafers are delivered to an inspection station that captures a series of whole wafer images using simultaneous dark and bright field illumination. A full-color image of 100% of the wafer is captured and is known as a RGB signature. Such a signature has three elements: a red value, a green value, and a blue value that vary within a predetermined range such as 0-255. The resulting image or signature is compared to that of a “golden” wafer with no defects and a confidence score is assigned indicating how similar the signatures are. When a significant difference is detected, further analysis is performed to classify the defect so that appropriate remedial action can be performed.
One shortcoming of the prior art ADI systems is that they do not account for the tool-to-tool variability in lamp output, or intensity, among the different inspection tools. This variability affects the resulting RGB signature and its values. Thus, a wafer can have a signature that differs from the golden wafer image even if no misprocessing has occurred. This difference between a test wafer's image and the golden wafer image may mistakenly be attributed to a defect even when there is no defect actually present.
Another shortcoming is that when a new ADI tool arrives at a facility its factory settings may vary from the other tools already on the production line and this variance may be significant enough to cause errors when inspecting wafers. Such as, for example, determining that a wafer has a defect when one actually is not present on the wafer.